Instructions to use hf-internal-testing/tiny-random-yolos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-yolos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-internal-testing/tiny-random-yolos")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-yolos") model = AutoModelForObjectDetection.from_pretrained("hf-internal-testing/tiny-random-yolos") - Notebooks
- Google Colab
- Kaggle
Upload feature extractor
Browse files- preprocessor_config.json +18 -0
preprocessor_config.json
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{
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"do_normalize": true,
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"do_resize": true,
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"feature_extractor_type": "YolosFeatureExtractor",
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"format": "coco_detection",
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"image_mean": [
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0.485,
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0.456,
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0.406
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],
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"image_std": [
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0.229,
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0.224,
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0.225
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],
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"max_size": 1333,
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"size": 800
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}
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